• 대한교통학회지
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• 제27권3호
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• pp.71-77
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• 2009

유비쿼터스 교통환경이 구현되면 기존 ITS 환경에서는 불가능하였던, 개별차량 위치, 속도 등 미세한 데이터 수집이 가능해 지며, V2V(Vehicle-to-Vehicle), V2I(Vehicle-to-Infra) 양방통신이 가능해 짐에 따라 개별차량 혹은 차량군 단위의 미세 제어가 가능해 진다. 이러한 유비쿼터스 교통 환경의 장점에 입각하여 교통류 안정성을 지표로 하는 연속류 정체예방관리 방안이 선행연구에서 제시된 바 있다. 본 연구에서는 유비쿼터스 교통환경에서 정체예방관리를 실현함에 있어 제기된 쟁점사항들에 대하여, VISSIM 시뮬레이션 실험결과에 입각하여 해답을 제시하였다. 교통류 안정성을 명시적으로 교통류 관리에 적용할 수 있도록, 유비쿼터스 교통환경에서 수집 가능한 차량군 길이와 간격으로 도출하였다. 또한 교통상황에 따라 차별화된 운영관리가 필요하다는 타당성을 도출하고, 교통상황 구분 및 상황별 운영관리 방안을 제시하였다. 마지막으로 이러한 관리를 수행하였을 때 어떠한 잠재적 이익이 있는가를 보여주었다. 본 연구 결과는, 제반 제약조건으로 말미암아 제한적인 시뮬레이션 실험을 통해 도출되었다. 그러나 유비쿼터스 교통환경에서 새로운 개념의 교통관리를 시행하는 데 있어 그 타당성은 보여줄 수 있었다고 판단된다. 향후 보다 포괄적인 현장실험을 통해 제반 결과들이 확정되어야 할 것이다.

• 디지털산업정보학회논문지
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• 제18권2호
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• pp.9-16
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• 2022

The nodes constituting the vehicle ad hoc network (VANET) are vehicles moving along the road and road side units (RSUs) installed around the road. The vehicle ad hoc network is used to collect the status, speed, and location information of vehicles driving on the road, and to communicate with vehicles, vehicles, and RSUs. Today, as the number of vehicles continues to increase, urban roads are suffering from traffic jams, which cause various problems such as time, fuel, and the environment. In this paper, we propose a method to solve traffic congestion problems on urban roads and demonstrate that the method can be applied to solve traffic congestion problems through performance evaluation using two typical protocols of vehicle ad hoc networks, AODV and GPSR. The performance evaluation used ns-2 simulator, and the average number of traffic jams and the waiting time due to the average traffic congestion were measured. Through this, we demonstrate that the vehicle ad hoc-based traffic congestion management technique proposed in this paper can be applied to urban roads in smart cities.

• 인터넷정보학회논문지
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• 제6권3호
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• pp.147-158
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• 2005

나날이 심각해지는 교통문제에서 차량에 대한 정보를 이용하여 교통흐름을 개선해 줄 뿐만 아니라, 교통위반 차량을 효율적으로 적발할 수 있다. 차량 번호판은 차량정보를 인식하는데 중요하게 사용될 수 있다. 본 논문에서는 이동식 형태인 차량에 탑재한 카메라를 이용하여 촬영한 영상에서 차량의 번호판을 인식하는 새로운 기법을 제안한다. 여러 단계의 영상처리 과정과 인식 과정을 거쳐서 실시간에 처리할 수 있는 시스템으로 일반 차량뿐 아니라 특장차에 대한 인식도 가능하게 한다. 제안한 기법을 이용한 실제적 환경에서의 영상과 인식에 대한 결과가 실험결과에서 보여진다.

• 한국자동차공학회논문집
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• 제7권5호
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• pp.178-185
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• 1999

Recently, Collision Warning System is developed to improve vehicle safety. This system chiefly uses radar. But the detected vehicle from radar must be decide whether it is the vehicle in the same lane of my vehicle or not. Therefore, Vision System is needed to detect traffic lane. As a preparative step, this study presents the development of algorithm to recognize traffic lane curve direction. That is, the Neural Network that can recognize traffic lane curve direction is constructed by using the information of short distance, middle distance, and decline of traffic lane. For this procedure, the relation between used information and traffic lane curve direction must be analyzed. As the result of application to sampled 2,000 frames, the rate of success is over 90%.t text here.

• 한국정보과학회논문지:시스템및이론
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• 제30권11호
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• pp.610-620
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• 2003

다양한 그림자는 비젼 기반 차량 검출에서 오류를 발생시키는 주요 원인이다. 본 논문에서는 노면 표시 기반 방법과 배경 빼기 및 에지(BS & Edge) 방법이라는 두 가지 방안을 차량 검출과 그림자 제거를 위해 제안하였다. 노변의 지형 지물들로 인해서 발생하는 그림자의 영향이 크게 증가하는 상황에서의 실험을 통해서 96% 이상의 차량 검출 정확도를 나타냄을 확인하였다. 전술한 두 가지 방법을 기반으로 하여, 차량 추적, 차량 계수, 차종 분류, 그리고 속도 측정을 수행하여 각 차로의 부하를 나타내는 데 사용되는 차량 흐름과 관련된 여러 가지 교통 파라미터를 추출하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1689-1693
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• 2004

This paper proposes a vehicle detector with a magnetoresistive (MR) sensor. The detector consists of a MR sensor and mechanical and electronic apparatuses. Composed of six magnetically variable resistors, the MR sensor senses disturbance of the earth's magnetic field caused by a moving vehicle over itself and then produces an output indicative of the moving vehicle. Experiments have been carried out with three stages. At the first stage, the outputs of the sensor have been analyzed to show the validity of the detector's circuit and the detecting method. At the second stage, the detector has been tested on a local highway in Korea. Through the field tests, the outputs of the detector in response to various kinds of moving vehicles have been collected and analyzed. At the final stage, to verify the performance of the detector, traffic volumes on the highway have been measured with the detector and compared with the exact traffic volumes in a highly congested traffic.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.872-876
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• 2007

Road traffic noise map is effective method to save cost and time for environmental noise assessment. Generally, noise is calculated by using theoretical equation of noise prediction, and the calculated result can be influenced by various input factors. Especially, domestic vehicle classification method for traffic flow and heavy vehicle percentage is different from that of foreign countries. Thus, this can cause effect on the noise prediction results. In this study, noise prediction results by using domestic vehicle classification method are compared with those by foreign methods.

• 한국소음진동공학회논문집
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• 제22권2호
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• pp.193-197
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• 2012

Road traffic noise map is effective method to save cost and time for environmental noise assessment. Generally, noise is calculated by using theoretical equation of noise prediction, and the calculated result can be influenced by various input factors. Especially, domestic vehicle classification method for traffic flow and heavy vehicle percentage is different from that of foreign countries. Thus, this can cause effect on the noise prediction results. In this study, noise prediction results by using domestic vehicle classification method are compared with those by foreign methods.

• 전자공학회논문지B
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• 제30B권6호
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• pp.100-108
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• 1993

In this paper, noticing the point of human's ability which appropriately cope with vague conditions, we design fuzzy traffic signal light controller similar to human's distinction ability and decide the optimum cycle most suited to any traffic junction using fuzzy identification algorithm. In this study, for the control output decision process we design fuzzy controller better than electronic vehicle actuated controller in performance. We propose the cycle decision method which is not limited by the variance of traffic junction vehicle number through overcoming the limit of Webster's method which is adopted by the fixed cycle controller. Simulated experimental results show that fuzzy controller and fuzzy identification algorithm are better than the existing electronic vehicle actuated controller and fixed cycle controller in delay time per vehicle.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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• pp.66-71
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• 2003

In the past, when there were few vehicles on the road, the T.O.D.(Time of Day) traffic signal worked very well. The T.O.D. signal operates on a preset signal cycling which cycles on the basis of the average number of average passenger cars in the memory device of an electric signal unit. Today, with increasing traffic and congested roads, the conventional traffic light creates startup-delay time and end lag time so that thirty to forty-five percent efficiency in traffic handling is lost, as well as adding to fuel costs. To solve this problem, this paper proposes a new concept of optimal green time algorithm, which reduces average vehicle waiting time while improving average vehicle speed using fuzzy rules and neural networks. Through computer simulation, this method has been proven to be much more efficient than fixed time interval signals. Fuzzy Neural Network will consistanly improve average waiting time, vehicle speed, and fuel consumption.